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Excel 2016 for Engineering Statistics: A Guide to Solving Practical Problems 1st ed. 2016 [Pehme köide]

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  • Formaat: Paperback / softback, 248 pages, kõrgus x laius: 235x155 mm, kaal: 4524 g, 161 Illustrations, color; 1 Illustrations, black and white; XV, 248 p. 162 illus., 161 illus. in color., 1 Paperback / softback
  • Sari: Excel for Statistics
  • Ilmumisaeg: 27-Jul-2016
  • Kirjastus: Springer International Publishing AG
  • ISBN-10: 331939181X
  • ISBN-13: 9783319391816
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Excel 2016 for Engineering Statistics: A Guide to Solving Practical Problems 1st ed. 2016Suurem pilt
  • Formaat: Paperback / softback, 248 pages, kõrgus x laius: 235x155 mm, kaal: 4524 g, 161 Illustrations, color; 1 Illustrations, black and white; XV, 248 p. 162 illus., 161 illus. in color., 1 Paperback / softback
  • Sari: Excel for Statistics
  • Ilmumisaeg: 27-Jul-2016
  • Kirjastus: Springer International Publishing AG
  • ISBN-10: 331939181X
  • ISBN-13: 9783319391816
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9783319391816.html
Märksõnad:
This book shows the capabilities of Microsoft Excel in teaching engineering statistics effectively. Similar to the previously published Excel 2013 for Engineering Statistics , this book is a step-by-step exercise-driven guide for students and practitioners who need to master Excel to solve practical engineering problems. If understanding statistics isn"t your strongest suit, you are not especially mathematically-inclined, or if you are wary of computers, this is the right book for you.Excel, a widely available computer program for students and managers, is also an effective teaching and learning tool for quantitative analyses in engineering courses. Its powerful computational ability and graphical functions make learning statistics much easier than in years past. However, Excel 2016 for Engineering Statistics: A Guide to Solving Practical Problems is the first book to capitalize on these improvements by teaching students and managers how to apply Excel to statistical techniques

necessary in their courses and work.Each chapter explains statistical formulas and directs the reader to use Excel commands to solve specific, easy-to-understand engineering problems. Practice problems are provided at the end of each chapter with their solutions in an appendix. Separately, there is a full Practice Test (with answers in an Appendix) that allows readers to test what they have learned.

Introduction.- Sample size, mean, standard deviation, standard error of the mean.- Random number generator.- Confidence interval about the mean using the TINV function and hypothesis testing.- One-group t-test for the mean.- Two-group t-test of the difference of the means for independent groups.- Correlation and simple linear regression.- Multiple correlation and multiple regression.- One-way analysis of variance (ANOVA).- Appendix A.- Appendix B.- Appendix C.- Appendix D.- Appendix E.- Index.
1 Sample Size, Mean, Standard Deviation, and Standard Error of the Mean
1(20)
1.1 Mean
1(1)
1.2 Standard Deviation
2(1)
1.3 Standard Error of the Mean
3(1)
1.4 Sample Size, Mean, Standard Deviation, and Standard Error of the Mean
4(8)
1.4.1 Using the Fill/Series/Columns Commands
4(1)
1.4.2 Changing the Width of a Column
5(1)
1.4.3 Centering Information in a Range of Cells
6(2)
1.4.4 Naming a Range of Cells
8(1)
1.4.5 Finding the Sample Size Using the =COUNT Function
9(1)
1.4.6 Finding the Mean Score Using the =AVERAGE Function
9(1)
1.4.7 Finding the Standard Deviation Using the =STDEV Function
10(1)
1.4.8 Finding the Standard Error of the Mean
10(2)
1.5 Saving a Spreadsheet
12(1)
1.6 Printing a Spreadsheet
13(2)
1.7 Formatting Numbers in Currency Format (Two decimal places)
15(2)
1.8 Formatting Numbers in Number Format (Three decimal places)
17(1)
1.9 End-of-Chapter Practice Problems
18(3)
References
20(1)
2 Random Number Generator
21(14)
2.1 Creating Frame Numbers for Generating Random Numbers
21(3)
2.2 Creating Random Numbers in an Excel Worksheet
24(2)
2.3 Sorting Frame Numbers into a Random Sequence
26(3)
2.4 Printing an Excel File So That All of the Information Fits onto One Page
29(3)
2.5 End-of-Chapter Practice Problems
32(3)
3 Confidence Interval About the Mean Using the TINV Function and Hypothesis Testing
35(30)
3.1 Confidence Interval About the Mean
35(11)
3.1.1 How to Estimate the Population Mean
35(1)
3.1.2 Estimating the Lower Limit and the Upper Limit of the 95% Confidence Interval About the Mean
36(1)
3.1.3 Estimating the Confidence Interval for the Chevy Impala in Miles Per Gallon
37(1)
3.1.4 Where Did the Number "1.96" Come From?
38(1)
3.1.5 Finding the Value for t in the Confidence Interval Formula
39(1)
3.1.6 Using Excel's TINV Function to Find the Confidence Interval About the Mean
40(1)
3.1.7 Using Excel to Find the 95% Confidence Interval for a Car's mpg Claim
40(6)
3.2 Hypothesis Testing
46(11)
3.2.1 Hypotheses Always Refer to the Population of Physical Properties that You Are Studying
47(1)
3.2.2 The Null Hypothesis and the Research (Alternative) Hypothesis
47(4)
3.2.3 The 7 Steps for Hypothesis-Testing Using the Confidence Interval About the Mean
51(6)
3.3 Alternative Ways to Summarize the Result of a Hypothesis Test
57(2)
3.3.1 Different Ways to Accept the Null Hypothesis
58(1)
3.3.2 Different Ways to Reject the Null Hypothesis
58(1)
3.4 End-of-Chapter Practice Problems
59(6)
References
63(2)
4 One-Group t-Test for the Mean
65(16)
4.1 The 7 STEPS for Hypothesis-Testing Using the One-Group t-Test
65(5)
4.1.1 STEP 1: State the Null Hypothesis and the Research Hypothesis
66(1)
4.1.2 STEP 2: Select the Appropriate Statistical Test
66(1)
4.1.3 STEP 3: Decide on a Decision Rule for the One-Group t-Test
66(1)
4.1.4 STEP 4: Calculate the Formula for the One-Group t-Test
67(1)
4.1.5 STEP 5: Find the Critical Value of t in the t-Table in Appendix E
68(1)
4.1.6 STEP 6: State the Result of Your Statistical Test
69(1)
4.1.7 STEP 7: State the Conclusion of Your Statistical Test in Plain English!
69(1)
4.2 One-Group t-Test for the Mean
70(5)
4.3 Can You Use Either the 95% Confidence Interval About the Mean OR the One-Group t-Test When Testing Hypotheses?
75(1)
4.4 End-of-Chapter Practice Problems
75(6)
References
79(2)
5 Two-Group t-Test of the Difference of the Means for Independent Groups
81(30)
5.1 The 9 STEPS for Hypothesis-Testing Using the Two-Group t-Test
82(9)
5.1.1 STEP 1: Name One Group, Group 1, and the Other Group, Group 2
82(1)
5.1.2 STEP 2: Create a Table That Summarizes the Sample Size, Mean Score, and Standard Deviation of Each Group
83(1)
5.1.3 STEP 3: State the Null Hypothesis and the Research Hypothesis for the Two-Group t-Test
84(1)
5.1.4 STEP 4: Select the Appropriate Statistical Test
84(1)
5.1.5 STEP 5: Decide on a Decision Rule for the Two-Group t-Test
84(1)
5.1.6 STEP 6: Calculate the Formula for the Two-Group t-Test
85(1)
5.1.7 STEP 7: Find the Critical Value of t in the t-Table in Appendix E
85(1)
5.1.8 STEP 8: State the Result of Your Statistical Test
86(1)
5.1.9 STEP 9: State the Conclusion of Your Statistical Test in Plain English!
86(5)
5.2 Formula #1: Both Groups Have a Sample Size Greater Than 30
91(8)
5.2.1 An Example of Formula #1 for the Two-Group t-Test
92(7)
5.3 Formula #2: One or Both Groups Have a Sample Size Less Than 30
99(8)
5.4 End-of-Chapter Practice Problems
107(4)
References
109(2)
6 Correlation and Simple Linear Regression
111(46)
6.1 What Is a "Correlation?"
111(7)
6.1.1 Understanding the Formula for Computing a Correlation
116(1)
6.1.2 Understanding the Nine Steps for Computing a Correlation, r
116(2)
6.2 Using Excel to Compute a Correlation Between Two Variables
118(5)
6.3 Creating a Chart and Drawing the Regression Line onto the Chart
123(10)
6.3.1 Using Excel to Create a Chart and the Regression Line Through the Data Points
125(8)
6.4 Printing a Spreadsheet So That the Table and Chart Fit onto One Page
133(2)
6.5 Finding the Regression Equation
135(9)
6.5.1 Installing the Data Analysis ToolPak into Excel
136(3)
6.5.2 Using Excel to Find the SUMMARY OUTPUT of Regression
139(3)
6.5.3 Finding the Equation for the Regression Line
142(1)
6.5.4 Using the Regression Line to Predict the y-value for a Given x-value
143(1)
6.6 Adding the Regression Equation to the Chart
144(3)
6.7 How to Recognize Negative Correlations in the SUMMARY OUTPUT Table
147(1)
6.8 Printing Only Part of a Spreadsheet Instead of the Entire Spreadsheet
147(2)
6.8.1 Printing Only the Table and the Chart on a Separate Page
148(1)
6.8.2 Printing Only the Chart on a Separate Page
148(1)
6.8.3 Printing Only the SUMMARY OUTPUT of the Regression Analysis on a Separate Page
149(1)
6.9 End-of-Chapter Practice Problems
149(8)
References
155(2)
7 Multiple Correlation and Multiple Regression
157(16)
7.1 Multiple Regression Equation
157(3)
7.2 Finding the Multiple Correlation and the Multiple Regression Equation
160(4)
7.3 Using the Regression Equation to Predict FROSH GPA
164(1)
7.4 Using Excel to Create a Correlation Matrix in Multiple Regression
164(3)
7.5 End-of-Chapter Practice Problems
167(6)
References
172(1)
8 One-Way Analysis of Variance (ANOVA)
173(18)
8.1 Using Excel to Perform a One-way Analysis of Variance (ANOVA)
175(3)
8.2 How to Interpret the ANOVA Table Correctly
178(1)
8.3 Using the Decision Rule for the ANOVA F-test
178(1)
8.4 Testing the Difference Between Two Groups Using the ANOVA t-test
179(5)
8.4.1 Comparing Brand A vs. Brand C in Miles Driven Using the ANOVA t-test
180(4)
8.5 End-of-Chapter Practice Problems
184(7)
References
189(2)
Appendices
191(56)
Appendix A Answers to End-of-Chapter Practice Problems
191(32)
Appendix B Practice Test
223(10)
Appendix C Answers to Practice Test
233(10)
Appendix D Statistical Formulas
243(2)
Appendix E t-Table
245(2)
Index 247
At the beginning of his academic career, Prof. Tom J. Quirk spent six years in educational research at The American Institutes for Research and Educational Testing Service. He then taught Social Psychology, Educational Psychology, General Psychology, Marketing, Management, and Accounting at Principia College, and is currently a Professor of Marketing in the George Herbert Walker School of Business & Technology at Webster University based in St. Louis, Missouri (USA) where he teaches Marketing Statistics, Marketing Research, and Pricing Strategies. He has written 60+ textbook supplements in Marketing and Management, published 20+ articles in professional journals, and presented 20+ papers at professional meetings. He holds a B.S. in Mathematics from John Carroll University, both an M.A. in Education and a Ph.D. in Educational Psychology from Stanford University, and an M.B.A. from The University of Missouri-St. Louis.